Cloudera Developer Blog · QuickStart VM Posts
One of the common questions I get from students and developers in my classes relates to IDEs and MapReduce: How do you create a MapReduce project in Eclipse and then debug it?
To answer that question, I have created a screencast showing you how, using Cloudera’s QuickStart VM. The QuickStart VM helps developers get started writing MapReduce code without having to worry about software installs and configuration. Everything is installed and ready to go. You can download the image type that corresponds to your preferred virtualization platform.
OSCON 2013 is already receding in the rear-view mirror, but we had a great time. Cloudera’s sessions were very well attended — with Tom Wheeler taking the prize (well over 200 attendees for his “Introduction to Apache Hadoop” tutorial) — but best of all was the opportunity to meet and mingle with people in the broader open source community. If you visited us at Booth 420, we hope you will now download and install the QuickStart VM after seeing it in our demo, and that your questions were adequately answered (most popular question: “Can you tell me more about Cloudera Impala?”)
In my biased opinion, the crowning achievement was our ability to not only distribute a couple hundred “Data is the New Bacon” Tshirts within a 36-hour period, but to clean ourselves out of the meat-free version shortly thereafter, as well:
For years, Cloudera has provided virtual machines that give you a working Apache Hadoop environment out-of-the-box. It’s the quickest way to learn and experiment with Hadoop right from your desktop.
We’re constantly updating and improving the QuickStart VM, and in the latest release there are two of Cloudera’s new products that give you easier and faster access to your data: Cloudera Search and Cloudera Impala. We’ve also added corresponding applications to Hue – an open source web-based interface for Hadoop, and the easiest way to interact with your data.
Cloudera Search integrates Apache Solr with the rest of the platform, to let you do full-text search of the data stored in your cluster, just like you would with an online search-engine! Cloudera Impala, on the other hand, lets you execute SQL queries against that same data, on the same platform, and get results back fast enough to interactively explore and analyze. With both these workloads available on the cluster, it eliminates the pain of having to move large data sizes around.